arXiv subjects

Chia-Ching Lin

Publications and source records attributed to Chia-Ching Lin.

12 recordsLinked to original sources

arXiv2024

Learning with Instance-Dependent Noisy Labels by Anchor Hallucination and Hard Sample Label Correction

Learning from noisy-labeled data is crucial for real-world applications. Traditional Noisy-Label Learning (NLL) methods categorize training data into clean and noisy sets based on the loss distribution of training samples. However, they often neglect that clean samples, especially those with intricate visual patterns, may also yield substantial losses. This oversight is particularly significant in datasets with Instance-Dependent Noise (IDN), where mislabeling probabilities correlate with visual appearance. Our approach explicitly distinguishes between clean vs.noisy and easy vs. hard samples. We identify training samples with small losses, assuming they have simple patterns and correct labels. Utilizing these easy samples, we hallucinate multiple anchors to select hard samples for label correction. Corrected hard samples, along with the easy samples, are used as labeled data in subsequent semi-supervised training. Experiments on synthetic and real-world IDN datasets demonstrate the superior performance of our method over other state-of-the-art NLL methods.

cs.CV↗

arXiv2024

Improving Limited Supervised Foot Ulcer Segmentation Using Cross-Domain Augmentation

Diabetic foot ulcers pose health risks, including higher morbidity, mortality, and amputation rates. Monitoring wound areas is crucial for proper care, but manual segmentation is subjective due to complex wound features and background variation. Expert annotations are costly and time-intensive, thus hampering large dataset creation. Existing segmentation models relying on extensive annotations are impractical in real-world scenarios with limited annotated data. In this paper, we propose a cross-domain augmentation method named TransMix that combines Augmented Global Pre-training AGP and Localized CutMix Fine-tuning LCF to enrich wound segmentation data for model learning. TransMix can effectively improve the foot ulcer segmentation model training by leveraging other dermatology datasets not on ulcer skins or wounds. AGP effectively increases the overall image variability, while LCF increases the diversity of wound regions. Experimental results show that TransMix increases the variability of wound regions and substantially improves the Dice score for models trained with only 40 annotated images under various proportions.

cs.CV↗

arXiv2023

All-electrical detection of the spin-charge conversion in nanodevices based on SrTiO3 two-dimensional electron gases

The Magnetoelectric Spin-Orbit (MESO) technology aims to bring logic into memory by combining a ferromagnet with a magnetoelectric (ME) element for information writing, and a spin-orbit (SO) element for information read-out through spin-charge conversion. Among candidate SO materials to achieve a large MESO output signal, oxide Rashba two-dimensional electron gases (2DEGs) have shown very large spin-charge conversion efficiencies, albeit mostly in spin-pumping experiments. Here, we report all-electrical spin-injection and spin-charge conversion experiments in nanoscale devices harnessing the inverse Edelstein effect of SrTiO3 2DEGs. We have designed, patterned and fabricated nanodevices in which a spin current injected from a cobalt layer into the 2DEG is converted into a charge current. We optimized the spin-charge conversion signal by applying back-gate voltages, and studied its temperature evolution. We further disentangled the inverse Edelstein contribution from spurious effects such as the planar Hall effect, the anomalous Hall effect or the anisotropic magnetoresistance. The combination of non-volatility and high energy efficiency of these devices could potentially lead to new technology paradigms for beyond-CMOS computing architectures.

cond-mat.mes-hall↗

arXiv2023

Voltage-based magnetization switching and reading in magnetoelectric spin-orbit nanodevices

As CMOS technologies face challenges in dimensional and voltage scaling, the demand for novel logic devices has never been greater, with spin-based devices offering scaling potential, at the cost of significantly high switching energies. Alternatively, magnetoelectric materials are predicted to enable low-power magnetization control, a solution with limited device-level results. Here, we demonstrate voltage-based magnetization switching and reading in nanodevices at room temperature, enabled by exchange coupling between multiferroic BiFeO$_3$ and ferromagnetic CoFe, for writing, and spin-to-charge current conversion between CoFe and Pt, for reading. We show that upon the electrical switching of the BiFeO$_3$, the magnetization of the CoFe can be reversed, giving rise to different voltage outputs. Through additional microscopy techniques, magnetization reversal is linked with the polarization state and antiferromagnetic cycloid propagation direction in the BiFeO$_3$. This study constitutes the building block for magnetoelectric spin-orbit logic, opening a new avenue for low-power beyond-CMOS technologies.

cond-mat.mes-hall↗

arXiv2022

All-electrical spin-to-charge conversion in sputtered Bi$_x$Se$_{1-x}$

One of the major obstacles to realizing spintronic devices such as MESO logic devices is the small signal magnitude used for magnetization readout, making it important to find materials with high spin-to-charge conversion efficiency. Although intermixing at the junction of two materials is a widely occurring phenomenon, its influence on material characterization and the estimation of spin-to-charge conversion efficiencies is easily neglected or underestimated. Here, we demonstrate all electrical spin-to-charge conversion in Bi$_x$Se$_{1-x}$ nanodevices and show how the conversion efficiency can be overestimated by tens of times depending on the adjacent metal used as a contact. We attribute this to the intermixing-induced compositional change and the properties of a polycrystal that lead to drastic changes in resistivity and spin Hall angle. Strategies to improve the spin-to-charge conversion signal in similar structures for functional devices are discussed.

cond-mat.mes-hall↗

arXiv2022

Domain-Generalized Textured Surface Anomaly Detection

Anomaly detection aims to identify abnormal data that deviates from the normal ones, while typically requiring a sufficient amount of normal data to train the model for performing this task. Despite the success of recent anomaly detection methods, performing anomaly detection in an unseen domain remain a challenging task. In this paper, we address the task of domain-generalized textured surface anomaly detection. By observing normal and abnormal surface data across multiple source domains, our model is expected to be generalized to an unseen textured surface of interest, in which only a small number of normal data can be observed during testing. Although with only image-level labels observed in the training data, our patch-based meta-learning model exhibits promising generalization ability: not only can it generalize to unseen image domains, but it can also localize abnormal regions in the query image. Our experiments verify that our model performs favorably against state-of-the-art anomaly detection and domain generalization approaches in various settings.

cs.CV↗

arXiv2021

Physics-Based Models for Magneto-Electric Spin-Orbit Logic Circuits

Spintronic devices are a promising beyond-CMOS device option thanks to their energy efficiency and compatibility with CMOS. To accurately capture their multi-physics dynamics, a rigorous treatment of both spin and charge and their inter-conversion is required. Here we present physics-based device models based on 4x4 matrices for the spin-orbit coupling part of the magneto-electric spin-orbit (MESO) device. Also, a more rigorous physics model of ferroelectric and magnetoelectric switching of ferromagnets, based on Landau-Lifshitz-Gilbert (LLG) and Landau-Khalatnikov (LK) equations, is presented. With the combined model implemented in a SPICE circuit simulator environment, simulation results were obtained which show feasibility of MESO implementation and functional operation of buffers, oscillators, and majority gates.

cond-mat.mes-hall↗

arXiv2021

Spin-charge interconversion in KTaO$_3$ two-dimensional electron gases

Oxide interfaces exhibit a broad range of physical effects stemming from broken inversion symmetry. In particular, they can display non-reciprocal phenomena when time reversal symmetry is also broken, e.g., by the application of a magnetic field. Examples include the direct and inverse Edelstein effects (DEE, IEE) that allow the interconversion between spin currents and charge currents. The DEE and IEE have been investigated in interfaces based on the perovskite SrTiO$_3$ (STO), albeit in separate studies focusing on one or the other. The demonstration of these effects remains mostly elusive in other oxide interface systems despite their blossoming in the last decade. Here, we report the observation of both the DEE and IEE in a new interfacial two-dimensional electron gas (2DEG) based on the perovskite oxide KTaO$_3$. We generate 2DEGs by the simple deposition of Al metal onto KTaO$_3$ single crystals, characterize them by angle-resolved photoemission spectroscopy and magnetotransport, and demonstrate the DEE through unidirectional magnetoresistance and the IEE by spin-pumping experiments. We compare the spin-charge interconversion efficiency with that of STO-based interfaces, relate it to the 2DEG electronic structure, and give perspectives for the implementation of KTaO$_3$ 2DEGs into spin-orbitronic devices.

cond-mat.mes-hall↗

arXiv2021

Metal/SrTiO$_3$ two-dimensional electron gases for spin-to-charge conversion

SrTiO$_3$-based two-dimensional electron gases (2DEGs) can be formed through the deposition of epitaxial oxides like LaAlO$_3$ or of reactive metals such as Al. Such 2DEGs possess a finite Rashba spin-orbit coupling that has recently been harnessed to interconvert charge and spin currents through the direct and inverse Edelstein and spin Hall effects. Here we compare the formation and properties of 2DEGs generated in SrTiO$_3$ by the growth of Al, Ta and Y ultrathin films by magnetron sputtering. By combining in situ and ex situ X-ray photoelectron spectroscopy (XPS) we gain insight into the reduction of the SrTiO$_3$ and the appearance of Ti$^{3+}$ states associated with 2DEG formation, its reoxidation by exposure to the air, and the transformation of the metal into its binary oxides. We extract the carrier densities through magnetotransport and compare them with the XPS data. Finally, working with samples covered by an extra layer of NiFe, we perform spin-pumping ferromagnetic resonance experiments and investigate spin-charge conversion as a function of gate voltage. We identify trends in the data across the different sample systems and discuss them as a function of the carrier density and the transparency of the metal oxide tunnel barrier.

cond-mat.mes-hall↗

arXiv2020

A Detailed Look At CNN-based Approaches In Facial Landmark Detection

Facial landmark detection has been studied over decades. Numerous neural network (NN)-based approaches have been proposed for detecting landmarks, especially the convolutional neural network (CNN)-based approaches. In general, CNN-based approaches can be divided into regression and heatmap approaches. However, no research systematically studies the characteristics of different approaches. In this paper, we investigate both CNN-based approaches, generalize their advantages and disadvantages, and introduce a variation of the heatmap approach, a pixel-wise classification (PWC) model. To the best of our knowledge, using the PWC model to detect facial landmarks have not been comprehensively studied. We further design a hybrid loss function and a discrimination network for strengthening the landmarks' interrelationship implied in the PWC model to improve the detection accuracy without modifying the original model architecture. Six common facial landmark datasets, AFW, Helen, LFPW, 300-W, IBUG, and COFW are adopted to train or evaluate our model. A comprehensive evaluation is conducted and the result shows that the proposed model outperforms other models in all tested datasets.

cs.CV↗

arXiv2020

Spin-orbit magnetic state readout in scaled ferromagnetic/heavy metal nanostructures

Efficient detection of the magnetic state at nanoscale dimensions is an important step to utilize spin logic devices for computing. Magnetoresistance effects have been hitherto used in magnetic state detection, but they suffer from energetically unfavorable scaling and do not generate an electromotive force that can be used to drive a circuit element for logic device applications. Here, we experimentally show that a favorable miniaturization law is possible via the use of spin-Hall detection of the in-plane magnetic state of a magnet. This scaling law allows us to obtain a giant signal by spin Hall effect in CoFe/Pt nanostructures and quantify an effective spin-to-charge conversion rate for the CoFe/Pt system. The spin-to-charge conversion can be described as a current source with an internal resistance, i.e., it generates an electromotive force that can be used to drive computing circuits. We predict that the spin-orbit detection of magnetic states can reach high efficiency at reduced dimensions, paving the way for scalable spin-orbit logic devices and memories.

cond-mat.mes-hall↗

arXiv2018

Voltage Control of Uni-directional Anisotropy in Ferromagnet-Multiferroic System

Demonstration of ultra-low energy switching mechanisms is an imperative for continued improvements in computing devices. Ferroelectric (FE) and multiferroic (MF) orders and their manipulation promises an ideal combination of state variables to reach atto-Joule range for logic and memory (i.e., ~ 30X lower switching energy than nanoelectronics). In BiFeO3 the coupling between the antiferromagnetic (AFM) and FE orders is robust at room temperature, scalable in voltage, stabilized by the FE order, and can be integrated into a fabrication process for a beyond-CMOS era. The presence of the AFM order and a canted magnetic moment in this system causes exchange interaction with a ferromagnet such as CoFe or LSMO. While previous work has shown that exchange coupling (uniaxial anisotropy) can be controlled with an electric field, several puzzling issues remain. Perhaps the most intriguing among them is that the BiFeO3-CoFe bilayer did not demonstrate any electrically controlled directional anisotropy, i.e., an exchange bias, which is a potential mechanism for 180o magnetic reversal and is independent of switching kinetics. However, what is needed/preferred for logic and memory is a magneto-electric mechanism that works analogous to an applied field, i.e a uni-directional anisotropy that is voltage modulated. Here, we present the evidence of electrical control of exchange bias of a laterally scaled spin valve that is exchange-coupled to BiFeO3 at room temperature. We show that the exchange bias in this bilayer is thermally robust, electrically controlled and reversible. We anticipate that magneto-electricity at such scaled dimensions provides a powerful pathway for computing beyond the modern nanoelectronics transistors by enabling a new class of non-volatile, ultra-low energy computing elements.

cond-mat.mes-hall↗